<template>
  <div class="bg"></div>
  <div class="box">
    <h3>第 {{ level }}关</h3>
    <div class="app">
      <div class="scene-container">
        <div class="scene-inner">
          <div
            v-for="(item, index) in scene"
            class="symbol"
            :key="item.id"
            :style="{
              transform: `translateX(${item.status === 0 ? item.x : item.status === 1 ? sortedQueue[item.id] : -1000}%) translateY(${item.status === 0 ? item.y : 1050}%)`,
              opacity: item.status < 2 ? 1 : 0
            }"
            @click="clickSymbol(index)"
          >
            <div class="symbol-inner" :style="{ backgroundColor: item.isCover ? '#999' : 'white' }">
              <span></span>
              <div class="content">
                <!-- <h2>Hover me!</h2> -->
              </div>
              <img style="width: 100%" :src="item.icon" alt="" />
            </div>
          </div>
        </div>
      </div>
      <div class="queue-container flex-container flex-center"></div>
      <div class="flex-container flex-between">
        <button class="flex-grow" @click="pop">弹出</button>
        <button class="flex-grow" @click="undo">撤销</button>
        <button class="flex-grow" @click="wash">洗牌</button>
        <button class="flex-grow" @click="levelUp">下一关</button>
      </div>
      <div class="modal" v-if="finished">
        <h1>{{ tipText }}</h1>
        <button @click="restart">亲我一口并再来一次</button>
      </div>
    </div>
  </div>
</template>

<script setup lang="ts">
import { ref, watchEffect } from 'vue'
import musice from '@/assets/ylgy.mp3'
import c1 from '@/assets/images/c-1.png'
import c2 from '@/assets/images/c-2.png'
import c3 from '@/assets/images/c-3.png'
import c4 from '@/assets/images/c-4.png'
import c5 from '@/assets/images/c-5.png'
import c6 from '@/assets/images/c-6.png'
import c7 from '@/assets/images/c-7.png'
import c8 from '@/assets/images/c-8.png'
import c9 from '@/assets/images/c-9.png'
import c10 from '@/assets/images/c-10.png'
import c11 from '@/assets/images/c-11.png'
import c12 from '@/assets/images/c-12.png'
import c13 from '@/assets/images/c-13.png'
import c14 from '@/assets/images/c-14.png'
import c15 from '@/assets/images/c-15.png'
import c16 from '@/assets/images/c-16.png'
import c17 from '@/assets/images/c-17.png'
import c18 from '@/assets/images/c-18.png'
import c19 from '@/assets/images/c-19.png'
// 生成随机id
const randomString: (len: number) => string = (len) => {
  const pool = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
  let res = ''
  while (len >= 0) {
    res += pool[Math.floor(pool.length * Math.random())]
    len--
  }
  return res
}
//延时函数
const waitTimeout: (timeout: number) => Promise<void> = (timeout) => {
  return new Promise<void>((resolve) => {
    setTimeout(() => {
      resolve()
    }, timeout)
  })
}

// 初始icon数组
// 羊了个羊图片素材
// const icons = [
//   '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%0A2tHbdmQj7gj5Ri1oQFp+7CEIYMA7Q1IhjF0I3iGEN/zhF5+ugAAAOw==',
//   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J+Kl6BjHFfjhBAxSxRAu3gt7DUCINgjhFfF4CV/Uw%0A4f+fFkgGiZFD0VZyIQ2ztQsbWPkSCUmkBf6Cgx7yZgMZ/EAPcGAiJ5ETgNpq%0AakGe9BQcZHCIOhAiEBTI9AwmUIfD9gPMEWHAIinFLCmNYK45icAHtdMGBI+6%0AJCWMCAFu8WrCYPI9I6AhVMDhhaKYoQkUkOgMav2SRMBLIgYIxhc28Qha9WEM%0AiuiCJ14SY1FMAAKufsk5qrAGX0yD1kWpALnk1uVNeCCUGdHFBSYBEkdk4hNK%0AYAQjgqCEX8yjFgOZhFwK0IQQJBQqCmjHGgY+8CooIHdFESQXZpCrkpxAE45o%0AgAOk4IcokIAAV7gCCZDghw4EYcNfGU3ObnEDBbCCGi7/IDjBXcAKBcQDkPOx%0AUWldVQAhSOEScVCDzlOu8jW4QOfUUMY4vEurUB0pCZTixBE+UINj/yPnO++5%0Az3Wuhjj8AxANkEIWiOGqI2gLEA7oBQl60QINFEMCCIG6Gniu8p/r3OoEWQcy%0AtpEEAngAFw7nycEkona2r5zqcFcIH1KRjr1TpO9Sd3vVDe8TxPdc8YFn/ExK%0AQHW/D1zxoGik5FWiDipUPvFUVwMWULD5lEBBH9SgehmkjoPQqyEXS5BH6T0i%0AhzOE3vIEJwMLXF+PTsyeIhmQRS6ovgWpq3wDW3C9D34/EVBQnRpb8IXxe46D%0A3VM9G8yHyDJCjwDpT7/nZbC+wRrOkH2FWGH4Or/GBtawATJswQWr7zkZECB+%0AnWOh/AlJQOrVQI4zrEH3obcF6zdwred6OvcN+IcQ1uB5zGAF/7AEBqgGwzCA%0AZBCB0UAgCWgQHIANUPAPOoB+BjiB7Cd+ufAOwpCBEQEPVIcA+jAMoUcF/AAN%0A9BB65YCCEfGBaoAApMcB9hB6vvcPskB1y2eDECEMceAOA6ENQZgL9DAQxoAB%0AOncMROgRGZAAJcABBFEKsUAKU0iFVoiFA6GFXAgYAQEAOw==',
//   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dyYJJzNDeTIoAv8ZZlXEB2gsLl6QFLbXUCUSgWwDg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%0ADBPwC5uCjwyij/zojwAJCQNZkAeJkBI5kRRZkRYZFQEBADs=',
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//   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U2G9/u1iKzkJSy8whRFiRHAxzPAHKU3CbQvYA5X1V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%0AIAQP4AqokARf6ZgvAZmSSZmWiZmayZmeCZqquZqs2ZocEhAAOw==',
//   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+qdg7m/bDUJaPtVyEyFlUEgKa9Imf0VphfiDskGu9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%0AKJmaiZjq4IA0RpgwYhKbOZqkWZqmeZqomZqquZqs2ZqumRkBAQA7',
//   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q0sCIAXPfkoFQp/7wxUgygINQuXQxtXDFM/3BBoUg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%0AIxG8oAndgAXYIADvIJmTmRABAQA7',
//   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sz9KIl8s2A2mCk+Iyck6mFhEY9wjFDWfyVoixqVAQ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%0Ac+DqOauV7krGXTDukoj+X4ABAL5GO7zbm18LAAAAAElFTkSuQmCC',
//   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SCQgAOw==',
//   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9Du9i56pNVbqEcQsx1UtagYgpNMAlrShEE0wgHXZE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%0ATxEQADs=',
//   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o9OvQYpFAsLxggQVJEeEEc6q50jdYiEFK/GiL1kbC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%0ADnpIjBWhDS/wB0GQjMpYEebQjM8YjdZ4jdiYjdroiwEBADs=',
//   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JGgF7rdOMn5IkCfPqiBmkQxIIkKIZ20CDHhhABRYI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%0A0sABl5AE7vGCMCiDNGiDONiDPviDQBiEKBEQADs=',
//   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0s4F4ndwPGfPLFo288UjpgGV/0CHBXP5iIRCSi2x+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%0AMgiDAQEAOw==',
//   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OIQDQ+vGEW+pvCCQp4j46pquP7SNkIxsdSXLgEA98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%0AsUASsbAL8OWER7gKF2AJkkALVmiFWKiFXNiFYjiGUREQADs=',
//   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j5ARDxlHOUSJAFhHuJxya8GT5vGIUQp7FJCRgBzfU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%0AT4ADy9kDZIADT7ADTNmgJ/GgETqhFXqhGaqhIjqiJFqijxEQADs=',
//   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E8K89AEwMAbeVD0H+Yxp+MFcb1PiuL04Ii2OsD0gE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%0AoaANUMqlGeGlYGoCB3AAMnqmabqmbeqmerqnfNqnfvqnAxEQADs=',
//   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u+NUwi+XBh4nBrQepQAUMIgjYnhhn0+HnEKprwQbu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%0AsR57FgEBADs=',
//   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YbgEhVKGDZ0D5xhgg7TUUotrRquLLX4bEAJIBAh1g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%0A6EkQAQEAOw==',
//   '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%0A5rGIeWzj7WYPCAA7'
// ]
const icons = [c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16, c17, c18, c19]
// 设置最大随机关卡
const maxLevel = 50
// 以下感谢大佬们提供的算法
const makeScene = (level: any) => {
  // 获取当前关卡
  const curLevel = Math.min(maxLevel, level)
  // 获取当前关卡应该拥有的icon数量
  const iconPool = icons.slice(0, 2 * curLevel)
  // 算出偏移量范围具体细节范围
  const offsetPool = [0, 25, -25, 50, -50].slice(0, 1 + curLevel)
  //  最终的元数据数组
  const scene: any = []
  // 确定范围
  //在一般情下 translate 的偏移量，如果是百分比的话，是按照自身的宽度或者高度去计算的，所以最大的偏移范围是百分800%
  // 然后通过Math.random 会小于百分之八百
  // 所以就会形成当前区间的随机数
  const range = [
    [2, 6],
    [1, 6],
    [1, 7],
    [0, 7],
    [0, 8]
  ][Math.min(4, curLevel - 1)]
  const randomSet = (icon: string) => {
    // 求偏移量
    const offset = offsetPool[Math.floor(offsetPool.length * Math.random())]
    // 偏移求列数
    const row = range[0] + Math.floor((range[1] - range[0]) * Math.random())
    // 求偏移行数
    const column = range[0] + Math.floor((range[1] - range[0]) * Math.random())
    console.log(offset, row, column)
    // 生成元数据对象
    scene.push({
      isCover: false, // 默认都是没有被覆盖的
      status: 0, // 是否被选中的状态
      icon, // 图标
      id: randomString(4), // 生成随机id
      x: column * 100 + offset, //x 坐标
      y: row * 100 + offset // y坐标
    })
  }

  // 如果级别高了就加点icon 花哨一点
  let compareLevel = curLevel
  while (compareLevel > 0) {
    iconPool.push(...iconPool.slice(0, Math.min(10, 2 * (compareLevel - 5))))
    compareLevel -= 5
  }
  // 生成元数据，初始状态下 iconPool的内容少生 随着增加，就会越来越难
  for (const icon of iconPool) {
    for (let i = 0; i < 6; i++) {
      randomSet(icon)
    }
  }
  // 返回元数据
  return scene
}
// 洗牌
const washScene = (level: any, scene: any) => {
  // 洗牌的随机逻辑与初始化相同,不在赘述
  const updateScene = scene.slice().sort(() => Math.random() - 0.5)
  const offsetPool = [0, 25, -25, 50, -50].slice(0, 1 + level)
  const range = [
    [2, 6],
    [1, 6],
    [1, 7],
    [0, 7],
    [0, 8]
  ][Math.min(4, level - 1)]

  const randomSet = (symbol: any) => {
    const offset = offsetPool[Math.floor(offsetPool.length * Math.random())]
    const row = range[0] + Math.floor((range[1] - range[0]) * Math.random())
    const column = range[0] + Math.floor((range[1] - range[0]) * Math.random())
    symbol.x = column * 100 + offset
    symbol.y = row * 100 + offset
    symbol.isCover = false
  }
  //遍历初始化数组
  for (const symbol of updateScene) {
    // 碰见已经选中的不处理
    if (symbol.status !== 0) continue
    randomSet(symbol)
  }
}
const scene = ref(makeScene(1)) // 元数据
const level = ref(1) // 等级
const queue: any = ref([]) // 下方选中数据
const sortedQueue: any = ref({}) // 排序内容
const finished = ref(false) // 是否完成
const tipText = ref('') // 提示
const animating = ref(false) // 动画
// 检查是否被覆盖
const checkCover = (value: any) => {
  // 深拷贝一份
  const updateScene = value.slice()
  // 是否覆盖算法
  // 遍历所有的元数据
  // 双重for循环来找到每个元素的覆盖情况
  for (let i = 0; i < updateScene.length; i++) {
    // 当前item对角坐标
    const cur = updateScene[i]
    // 先假设他都不是覆盖的
    cur.isCover = false
    // 如果status 不为0 说明已经被选中了，不用再判断了
    if (cur.status !== 0) continue
    // 拿到坐标
    const { x: x1, y: y1 } = cur
    // 为了拿到他们的对角坐标，所以要加上100
    //之所以要加上100 是由于 他的总体是800% 也就是一个格子的换算宽度是100
    const x2 = x1 + 100,
      y2 = y1 + 100
    // 第二个来循环来判断他的覆盖情况
    for (let j = i + 1; j < updateScene.length; j++) {
      const compare = updateScene[j]
      if (compare.status !== 0) continue

      const { x, y } = compare
      // 处理交集也就是选中情况
      // 两区域有交集视为选中
      // 两区域不重叠情况取反即为交集
      if (!(y + 100 <= y1 || y >= y2 || x + 100 <= x1 || x >= x2)) {
        // 由于后方出现的元素会覆盖前方的元素，所以只要后方的元素被选中了，前方的元素就不用再判断了
        // 又由于双层循环第二层从j 开始，所以不用担心会重复判断
        cur.isCover = true
        break
      }
    }
  }
  scene.value = updateScene
}

// 弹出
const pop = () => {
  // 如果选中队列中没有数据那么就退出
  if (!queue.value.length) return
  const updateQueue = queue.value.slice()
  const symbol = updateQueue.shift()
  if (!symbol) return
  const find = scene.value.find((s: any) => s.id === symbol.id)
  if (find) {
    // 随机一个位置
    queue.value = updateQueue
    find.status = 0
    find.x = 100 * Math.floor(8 * Math.random())
    find.y = 700
    // 遮挡检测
    checkCover(scene.value)
  }
}
// 撤销
const undo = () => {
  // 和弹出相同逻辑
  // 只是返回的位置为原来位置
  if (!queue.value.length) return
  const updateQueue = queue.value.slice()
  const symbol = updateQueue.pop()
  if (!symbol) return
  const find = scene.value.find((s: any) => s.id === symbol.id)
  if (find) {
    queue.value = updateQueue
    find.status = 0
    checkCover(scene)
  }
}
// 洗牌
const wash = () => {
  checkCover(washScene(level.value, scene.value))
}

// 下一关
const levelUp = () => {
  if (level.value >= maxLevel) {
    return
  }
  finished.value = false
  level.value = level.value + 1
  queue.value = []
  // 初始化场景并且检查是否被覆盖
  checkCover(makeScene(level.value + 1))
}
// 重开
const restart = () => {
  // 初始化内容
  finished.value = false
  level.value = 1
  queue.value = []
  // 第一关初始化，并开启遮挡检查
  checkCover(makeScene(1))
}

// 点击item
const clickSymbol = async (idx: number) => {
  // 如果已经完成了，就不处理
  if (finished.value || animating.value) return
  // 拷贝一份Scene
  const symbol = scene.value[idx]
  // 覆盖了和已经在队列里的也不处理
  if (symbol.isCover || symbol.status !== 0) return
  //置为可以选中状态
  symbol.status = 1
  queue.value.push(symbol)
  // 制造动画效果中防止点击
  // animating.value = true
  //三百毫秒的延迟
  await waitTimeout(300)
  // 拿到与他匹配的所有icon
  const filterSame = queue.value.filter((sb: any) => sb.icon === symbol.icon)

  // 选中的三个配对成功表示已经是三连了
  if (filterSame.length === 3) {
    // 由于icon的类型一样，留下队列中的不一样的剩余内容重新赋值
    queue.value = queue.value.filter((sb: any) => sb.icon !== symbol.icon)
    // 隐藏iocn，dom
    for (const sb of filterSame) {
      const find = scene.value.find((i: any) => i.id === sb.id)
      // 将他们的状态变为2 通过opacity 属性 来隐藏icon
      if (find) find.status = 2
    }
  }

  // 当格子沾满了，那么久表示已经失败了
  if (queue.value.length === 7) {
    tipText.value = '失败了'
    finished.value = true
  }

  if (!scene.value.find((s: any) => s.status !== 2)) {
    // 如果完成所有关卡，那就过了所有关了
    if (level.value === maxLevel) {
      tipText.value = '完成挑战'
      finished.value = true
      return
    }
    //否则加一关
    level.value = level.value + 1
    queue.value = []
    // 重新初始化
    checkCover(makeScene(level.value + 1))
  } else {
    // 处理覆盖情况
    checkCover(scene.value)
  }
  // 动画结束
  animating.value = false
}
// 队列区排序
watchEffect(() => {
  const cache: any = {}
  // 通过当前的icon的标识，将相同的icon归纳到一块
  // 方便后续排序
  for (const symbol of queue.value) {
    if (cache[symbol.icon]) {
      cache[symbol.icon].push(symbol)
    } else {
      cache[symbol.icon] = [symbol]
    }
  }
  const temp = []
  for (const symbols of Object.values(cache)) {
    temp.push(...(symbols as any))
  }
  const updateSortedQueue: any = {}
  let x = 50
  // 拿到更新后的队列区数据，计算权重
  for (const symbol of temp) {
    updateSortedQueue[symbol.id] = x
    x += 100
  }
  //赋值 ，这个是为了将选中的排序后的内容移动到队列区
  sortedQueue.value = updateSortedQueue
  // 检查覆盖情况
  checkCover(scene.value)
})
</script>
<style>
@import './index.scss';
</style>
